To take advantage of the computational world, or the nearer term internet of things, we need to infuse smarts throughout our data collection networks. We need to employ up-front and intermediate filters, traffic cops, aggregators, pattern detectors, and intelligent agents. We need to get over being data hoarders, and have the astuteness to leave data behind.

Culture, mistrust of the data, lack of interest. These very human factors are adoption barriers for 46% of the respondents. Yet, these barriers aren’t new. Nor, confined to big data and advanced analytics. To change a culture, you need to bring proof to the table. And proof requires hands-on experimentation and real-world data. We need data to prove that we need data. How will we get that?

“…a business-to-business order gateway is supposed to be emitting System Heartbeat events every 15 minutes. The System Heartbeat events inform IT operations the gateway is up and running. The absence of a heartbeat event indicates a failure. If the order gateway is down, business customers are likely to place an order with a competitor.”

On Twitter yesterday, I mentioned an event-driven billing subsystem I’m currently working on. In that system, we’ll be generating a (standard) projected monthly invoice. The invoice generation starts when the party is approved for billing.

Invoice regeneration is triggered by a set of events, including a change in plan, the receipt of a payment, or the absence of the receipt of payment. In this subsystem, the absence of a receipt is a non-payment event.